{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "def trainadd(name):\n",
    "    data = pd.read_csv(name)\n",
    "    csv_df = pd.DataFrame(data)\n",
    "    array = csv_df.to_numpy()\n",
    "    n=0\n",
    "    a,b,c = 0,0,0\n",
    "    for i in array[:,1:2]:\n",
    "        if i>0.3:\n",
    "            array[n,1]=1\n",
    "            a+=1\n",
    "        elif i>0:\n",
    "            array[n,1]=2\n",
    "            b+=1\n",
    "        else:\n",
    "            array[n,1]=3\n",
    "            c+=1\n",
    "        n+=1\n",
    "    df = pd.DataFrame(array)\n",
    "    colname = list(csv_df)\n",
    "    df.columns = colname\n",
    "    index_name = list(df.values[:,0])\n",
    "    #去掉第一行（\"公司\"）\n",
    "    df = df.drop(labels=\"公司\",axis = 1)\n",
    "    #将公司名改为Index\n",
    "    df.index = index_name\n",
    "    print(a,b,c)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 3 8\n",
      "4 3 8\n",
      "5 1 9\n",
      "5 1 9\n",
      "5 2 8\n",
      "7 0 8\n",
      "7 0 8\n",
      "7 2 6\n",
      "7 3 5\n",
      "4 4 7\n",
      "5 2 8\n",
      "5 2 8\n",
      "5 3 7\n",
      "6 3 6\n",
      "7 2 6\n",
      "8 1 6\n",
      "8 1 6\n",
      "8 1 6\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>综合评分</th>\n",
       "      <th>总评名次</th>\n",
       "      <th>工人数</th>\n",
       "      <th>机器数</th>\n",
       "      <th>债券</th>\n",
       "      <th>工资系数</th>\n",
       "      <th>累计研发</th>\n",
       "      <th>累计分红</th>\n",
       "      <th>净资产</th>\n",
       "      <th>人均利润率</th>\n",
       "      <th>资本利润率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>飞翔2号</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>我的小白</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>突击队</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>just_play</th>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>霸气外露</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>天涯之星</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YYY.W</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>湖北经济学院创新管理A队</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>卡布奇诺</th>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>伍零壹玖</th>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>270 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              综合评分  总评名次  工人数  机器数  债券  工资系数  累计研发  累计分红  净资产  人均利润率  资本利润率\n",
       "飞翔2号             1     1    1    1   7     6     3     1    4      4      2\n",
       "我的小白             1     2    1    1   4     2    10     3    1      1      1\n",
       "突击队              1     3    1    1   6     3     3     3    2      2      3\n",
       "just_play        1     4    1    1   2     4     9     3    3      3      4\n",
       "霸气外露             2     5    1    1   3     1     3     2    7      6      7\n",
       "...            ...   ...  ...  ...  ..   ...   ...   ...  ...    ...    ...\n",
       "天涯之星             3    10   12   12  12     8    12    10   10     10     10\n",
       "YYY.W            3    10   12   12  12     8    12    10   10     10     10\n",
       "湖北经济学院创新管理A队     3    10   12   12  12     8    12    10   10     10     10\n",
       "卡布奇诺             3    14   11   10  10     8     1    10   14     14     14\n",
       "伍零壹玖             3    15    1   11  11     8    11    10   15     15     15\n",
       "\n",
       "[270 rows x 11 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total = []\n",
    "for i in range(2,11):\n",
    "    file_name = str(i)+'03.csv'\n",
    "    df = trainadd(file_name)\n",
    "    total.append(df)\n",
    "for i in range(2,11):\n",
    "    file_name = 'D:/Desktop/新建文件夹 (3)/13334/'+str(i)+\"03.csv\"\n",
    "    df = trainadd(file_name)\n",
    "    total.append(df)\n",
    "res = pd.concat(total)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = list(res.values[:,2:])\n",
    "y =list(res.values[:,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用支持向量机svm(rbf)来分类svc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC()"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = SVC(kernel='rbf')\n",
    "model.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "def trans(name):\n",
    "    data = pd.read_csv(name)\n",
    "    csv_df = pd.DataFrame(data)\n",
    "    array = csv_df.to_numpy()\n",
    "    n=0\n",
    "    for i in array[:,1:2]:\n",
    "        if i>0.3:\n",
    "            array[n,1]=1\n",
    "        elif i>0:\n",
    "            array[n,1]=2\n",
    "        else:\n",
    "            array[n,1]=3\n",
    "        n+=1\n",
    "    df = pd.DataFrame(array)\n",
    "    colname = list(csv_df)\n",
    "    df.columns = colname\n",
    "    index_name = list(df.values[:,0])\n",
    "    #去掉第一行（\"公司\"）\n",
    "    df = df.drop(labels=\"公司\",axis = 1)\n",
    "    #将公司名改为Index\n",
    "    df.index = index_name\n",
    "    X_test = list(df.values[:,2:])\n",
    "    y_test =list(df.values[:,0])\n",
    "    return X_test,y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8666666666666667\n",
      "[0.9333333333333333, 0.8, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.8666666666666667, 0.7333333333333333, 0.8]\n"
     ]
    }
   ],
   "source": [
    "scores = []\n",
    "for i in range(2,10):\n",
    "    file_name = 'D:/Desktop/新建文件夹 (3)/13331/'+str(i)+\"03.csv\"\n",
    "    X_test,y_test = trans(file_name)\n",
    "    score = model.score(X_test,y_test)\n",
    "    scores.append(score)\n",
    "print(np.mean(scores))\n",
    "print(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用支持向量机svm(linear与rbf)来分类svc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "使用13329比赛数据测试模型\n",
      "['linear', 'rbf']\n",
      "[0.8083333333333333, 0.8583333333333334]\n"
     ]
    }
   ],
   "source": [
    "test = []\n",
    "kernel = ['linear','rbf']\n",
    "for i in kernel:\n",
    "    model = SVC(kernel=str(i))\n",
    "    model = model.fit(X,y)\n",
    "    scores = []\n",
    "    for i in range(2,10):\n",
    "        file_name = 'D:/Desktop/新建文件夹 (3)/13329/'+str(i)+\"03.csv\"\n",
    "        X_test,y_test = trans(file_name)\n",
    "        score = model.score(X_test,y_test)\n",
    "        scores.append(score)\n",
    "    test.append(np.mean(scores))\n",
    "print(\"使用13329比赛数据测试模型\")\n",
    "print(kernel)\n",
    "print(test)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用支持向量机svm(poly)来分类svc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 调整C，固定degree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.8024691358024691, 0.8518518518518519, 0.8271604938271605, 0.8271604938271605, 0.8271604938271605, 0.8271604938271605, 0.8271604938271605, 0.8271604938271605, 0.8271604938271605, 0.8271604938271605]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "x_train,x_test,y_train,y_test = train_test_split(X,y,test_size=0.3)\n",
    "score = []\n",
    "\n",
    "c=np.linspace(1,30,10)\n",
    "\n",
    "for i in range(10):\n",
    "    model = SVC(kernel='poly',C=c[i],coef0=3)\n",
    "    model.fit(x_train,y_train)\n",
    "    score.append(model.score(x_test,y_test))\n",
    "print(score)\n",
    "\n",
    "\n",
    "plt.plot(c,score,color='red',label=\"degree=3\")\n",
    "plt.title('degree - score') \n",
    "plt.xlabel(\"Model C\")\n",
    "plt.ylabel(\"Model Score\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 固定C=10,调整degree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.8395061728395061, 0.8271604938271605, 0.8271604938271605, 0.8518518518518519, 0.8641975308641975, 0.8641975308641975, 0.8641975308641975, 0.8765432098765432, 0.8765432098765432, 0.8765432098765432]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "x_train,x_test,y_train,y_test = train_test_split(X,y,test_size=0.3)\n",
    "score = []\n",
    "\n",
    "\n",
    "for i in range(1,11):\n",
    "    model = SVC(kernel='poly',C=10,degree=i,coef0=3)\n",
    "    model.fit(x_train,y_train)\n",
    "    score.append(model.score(x_test,y_test))\n",
    "print(score)\n",
    "\n",
    "\n",
    "plt.plot(range(1,11),score,color='red',label=\"C=10\")\n",
    "plt.title('degree - score') \n",
    "plt.xlabel(\"Model Degree\")\n",
    "plt.ylabel(\"Model Score\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 得到结论 C=10,degree=3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7916666666666667\n",
      "[0.8666666666666667, 0.8666666666666667, 0.8, 0.8666666666666667, 0.8, 0.8, 0.6666666666666666, 0.6666666666666666]\n"
     ]
    }
   ],
   "source": [
    "scores = []\n",
    "model = SVC(kernel='poly',C=10,degree=3,coef0=3)\n",
    "model.fit(X,y)\n",
    "\n",
    "for i in range(2,10):\n",
    "    file_name = 'D:/Desktop/新建文件夹 (3)/13336/'+str(i)+\"03.csv\"\n",
    "    X_test,y_test = trans(file_name)\n",
    "    score = model.score(X_test,y_test)\n",
    "    scores.append(score)\n",
    "print(np.mean(scores))\n",
    "print(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 其他"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x24025974a90>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import make_blobs,make_circles,make_moons,make_classification\n",
    "from sklearn.svm import SVC\n",
    "%matplotlib inline\n",
    "\n",
    "#定义决策可视化函数\n",
    "def plot_svc_decision_function(model,ax=None):\n",
    "    if ax == None:\n",
    "        ax = plt.gca()\n",
    "    xlim = ax.get_xlim()\n",
    "    ylim = ax.get_ylim()\n",
    "    \n",
    "    axisx = np.linspace(xlim[0],xlim[1],30)\n",
    "    axisy = np.linspace(ylim[0],ylim[1],30)\n",
    "    \n",
    "    axisx,axisy = np.meshgrid(axisx,axisy)\n",
    "    xy = np.vstack([axisx.ravel(),axisy.ravel()]).T\n",
    "    \n",
    "    Z = model.decision_function(xy).reshape(axisx.shape)\n",
    "    \n",
    "    ax.contour(axisx,axisy,Z\n",
    "              ,colors = 'k'\n",
    "              ,levels = [-1,0,1]\n",
    "              ,linestyles = ['--','-','--']\n",
    "              )\n",
    "    ax.set_xlim(xlim)\n",
    "    ax.set_ylim(ylim)\n",
    "\n",
    "#创建数据\n",
    "data = make_moons(n_samples = 500,noise = 0.2,random_state=0)\n",
    "X = data[0]\n",
    "y = data[1]\n",
    "\n",
    "#绘制决策过程\n",
    "plt.figure(figsize = (20,6))\n",
    "plt.subplot(1,2,1)\n",
    "clf1 = SVC(kernel='rbf',C=0.5).fit(X,y)\n",
    "clf2 = SVC(kernel='rbf',C=10).fit(X,y)\n",
    "\n",
    "plt.scatter(X[:,0],X[:,1],c=y,cmap='rainbow',s=5)\n",
    "plot_svc_decision_function(clf1)\n",
    "plt.scatter(clf1.support_vectors_[:,0],clf1.support_vectors_[:,1],facecolor = 'none',edgecolor = 'k')#绘制支持向量\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.scatter(X[:,0],X[:,1],c=y,cmap='rainbow',s=5)\n",
    "plot_svc_decision_function(clf2)\n",
    "plt.scatter(clf2.support_vectors_[:,0],clf2.support_vectors_[:,1],facecolor = 'none',edgecolor = 'k')#绘制支持向量\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "5203f191fb92a3c9962196e3c1c9bdaa035148bbce8d7674a8a57fbc91212ce7"
  },
  "kernelspec": {
   "display_name": "Python 3.8.9 64-bit",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.9"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
